You can build intuition about whether a product will succeed using a simple heuristic: If there were another random user sitting beside me, would they understand this product well enough to use it? This question helps separate two things: - Your own ability (or willingness) to understand something. - The likely response of the broader market. Example: Berachain Even after spending time on it, it was hard to piece together what it actually does and how a normal user is supposed to enjoy the protocol beyond the usual DeFi activities. By intuition, if something is lowkey ponzu, it needs broad participation to keep the flywheel going. The masses have to “get it” enough to join in and stay in the game. So the real question becomes: If it’s already this hard for you to understand, how likely is it that the next user will understand it well enough to participate and keep the flywheel spinning? Sometimes this sounds like cope for “not trying hard enough,” but markets are made of humans. If you don’t really understand it, there’s a good chance most others don’t either. When complexity is actually good There are situations where it does make sense to push through the complexity. If the “alpha” comes from you understanding something before the crowd, and that understanding lets you capture value directly, then putting in extra effort is rational. In that case, the payoff accrues mostly to you, so the complexity is part of the edge. When you need the masses But if the value of the product or protocol depends on collective participation, then it’s not just about your understanding. You also need: - The average user to understand it enough to act. - The average user to have enough agency and motivation to keep participating. - This is more like teamwork: the system only works if enough people can grok it and stay engaged. Because of that, you can sometimes skip deep data analysis and instead use this heuristic to quickly: - Guesstimate interest, engagement, and activity. - Spot potential headwinds early (e.g., too complex, unclear value, confusing incentives). Attention spans and bottlenecks On CT, where attention spans are basically those of goldfish, anything that requires heavy cognitive load usually gets forgotten fast. If excitement is truly high (think OHM), users will naturally compress the complexity into simple memes or rules of thumb. Those memes reveal: - How people mentally model the protocol. - Where the real flow and bottlenecks are. With Berachain, reading the docs, the rough takeaway became: to enjoy BERA, you often end up needing to dump BERA to be rewarded. That hints at a bottleneck in flows: BERA exists mainly to be sold. That’s not a great sign for sustainable value and therefore you should be careful going long on it (Perhaps this is one way to tell if the hype is about to end) In any case Everytime a meta is nearing the end of its lifespan, you typically see increase in complexity as new entrants try to incrementally improve the previous market leader with a lot more complexity, then the user gets tired and simplify things. Often, the simplified thesis is the pivot point. This data you can track. If the measure of the simplified thesis flame out then you can say the meta is kinda dead.